CEntRE: A paragraph-level Chinese dataset for Relation Extraction among Enterprises
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Abstract (arXiv)
Enterprise relation extraction aims to detect pairs of enterprise entities and identify the business relations between them from unstructured or semi-structured text data, and it is crucial for several real-world applications such as risk analysis, rating research and supply chain security. However, previous work mainly focuses on getting attribute information about enterprises like personnel and corporate business, and pays little attention to enterprise relation extraction. To encourage further progress in the research, we introduce the CEntRE, a new dataset constructed from publicly available business news data with careful human annotation and intelligent data processing. Extensive experiments on CEntRE with six excellent models demonstrate the challenges of our proposed dataset.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 37 references that are in the map. First posted on arXiv 19 Oct 2022.
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References · 17
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5 more
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